Static Scenes with Dynamic Perceptions

Static Scenes with Dynamic Perceptions

    Presenter(s)

    Kunal Agrawal

    Comments

    10:20-10:40, LTC Studio

    Description

    In this paper, we explore how computers can recognize motion illusions in static images—pictures that trick our eyes into seeing movement. To study this, we created a new dataset called MISS, which includes images with and without motion illusions. We tested advanced deep learning models to see how well they could identify these illusions and also checked whether color plays an important role. Our results show that these models are good at spotting motion illusions, especially when the images are in color. This highlights the importance of color in helping machines understand motion in still pictures.

    Publication Date

    4-23-2025

    Project Designation

    Graduate Research

    Primary Advisor

    Tam Nguyen

    Primary Advisor's Department

    Computer Science

    Keywords

    Stander Symposium, College of Arts and Sciences

    Institutional Learning Goals

    Community; Diversity; Scholarship

    Static Scenes with Dynamic Perceptions

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